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/**
* Marlin 3D Printer Firmware
* Copyright (C) 2016 MarlinFirmware [https://github.com/MarlinFirmware/Marlin]
*
* Based on Sprinter and grbl.
* Copyright (C) 2011 Camiel Gubbels / Erik van der Zalm
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
/**
* Least Squares Best Fit By Roxy and Ed Williams
*
8 years ago
* This algorithm is high speed and has a very small code footprint.
* Its results are identical to both the Iterative Least-Squares published
* earlier by Roxy and the QR_SOLVE solution. If used in place of QR_SOLVE
* it saves roughly 10K of program memory. It also does not require all of
* coordinates to be present during the calculations. Each point can be
* probed and then discarded.
*
*/
#include "MarlinConfig.h"
8 years ago
#if ENABLED(AUTO_BED_LEVELING_UBL) // Currently only used by UBL, but is applicable to Grid Based (Linear) Bed Leveling
#include "macros.h"
#include <math.h>
#include "least_squares_fit.h"
void incremental_LSF_reset(struct linear_fit_data *lsf) {
lsf->n = 0;
lsf->A = 0.0; // probably a memset() can be done to zero
lsf->B = 0.0; // this whole structure
lsf->D = 0.0;
lsf->xbar = lsf->ybar = lsf->zbar = 0.0;
lsf->x2bar = lsf->y2bar = lsf->z2bar = 0.0;
lsf->xybar = lsf->xzbar = lsf->yzbar = 0.0;
lsf->max_absx = lsf->max_absy = 0.0;
8 years ago
}
void incremental_LSF(struct linear_fit_data *lsf, float x, float y, float z) {
lsf->xbar += x;
lsf->ybar += y;
lsf->zbar += z;
lsf->x2bar += x*x;
lsf->y2bar += y*y;
lsf->z2bar += z*z;
lsf->xybar += x*y;
lsf->xzbar += x*z;
lsf->yzbar += y*z;
lsf->max_absx = (fabs(x) > lsf->max_absx) ? fabs(x) : lsf->max_absx;
lsf->max_absy = (fabs(y) > lsf->max_absy) ? fabs(y) : lsf->max_absy;
lsf->n++;
return;
}
int finish_incremental_LSF(struct linear_fit_data *lsf) {
float DD, N;
N = (float) lsf->n;
lsf->xbar /= N;
lsf->ybar /= N;
lsf->zbar /= N;
lsf->x2bar = lsf->x2bar/N - lsf->xbar*lsf->xbar;
lsf->y2bar = lsf->y2bar/N - lsf->ybar*lsf->ybar;
lsf->z2bar = lsf->z2bar/N - lsf->zbar*lsf->zbar;
lsf->xybar = lsf->xybar/N - lsf->xbar*lsf->ybar;
lsf->yzbar = lsf->yzbar/N - lsf->ybar*lsf->zbar;
lsf->xzbar = lsf->xzbar/N - lsf->xbar*lsf->zbar;
DD = lsf->x2bar*lsf->y2bar - lsf->xybar*lsf->xybar;
if (fabs(DD) <= 1e-10*(lsf->max_absx+lsf->max_absy))
return -1;
lsf->A = (lsf->yzbar*lsf->xybar - lsf->xzbar*lsf->y2bar) / DD;
lsf->B = (lsf->xzbar*lsf->xybar - lsf->yzbar*lsf->x2bar) / DD;
lsf->D = -(lsf->zbar + lsf->A*lsf->xbar + lsf->B*lsf->ybar);
return 0;
}
#endif